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ECNU at SemEval-2016 task 5: Extracting effective features from relevant fragments in sentence for aspect-based sentiment analysis in reviews

  • Mengxiao Jiang
  • , Zhihua Zhang
  • , Man Lan
  • East China Normal University
  • Shanghai Key Laboratory of Multidimensional Information Processing

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

This paper describes our systems submitted to the Sentence-level and Text-level Aspect-Based Sentiment Analysis (ABSA) task (i.e., Task 5) in SemEval-2016. The task involves two phases, namely, Aspect Detection phase and Sentiment Polarity Classification phase. We participated in the second phase of both subtasks in laptop and restaurant domains, which focuses on the sentiment analysis based on the given aspect. In this task, we extracted four types of features (i.e., Sentiment Lexicon Features, Linguistic Features, Topic Model Features and Word2vec Feature) from certain fragments related to aspect rather than the whole sentence. Then the proposed features are fed into supervised classifiers for sentiment analysis. Our submissions rank above average.

源语言英语
主期刊名SemEval 2016 - 10th International Workshop on Semantic Evaluation, Proceedings
出版商Association for Computational Linguistics (ACL)
361-366
页数6
ISBN(电子版)9781941643952
DOI
出版状态已出版 - 2016
活动10th International Workshop on Semantic Evaluation, SemEval 2016 co-located with the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2016 - San Diego, 美国
期限: 16 6月 201617 6月 2016

出版系列

姓名SemEval 2016 - 10th International Workshop on Semantic Evaluation, Proceedings

会议

会议10th International Workshop on Semantic Evaluation, SemEval 2016 co-located with the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2016
国家/地区美国
San Diego
时期16/06/1617/06/16

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